The dataset operators prepare the data for training an AutoML model in Vertex AI. For more details about specific data type dataset information, see Train and use your own models. For information about AutoML training in Vertex AI, see the AutoML training documentation. For information about Google Cloud Pipeline Components related to AutoML models and workflows, see Vertex AI AutoML components.
The Google Cloud Pipeline Components SDK includes the following operators related to
AutoML dataset
resource management:
-
GetVertexDatasetOp
-
ImageDatasetCreateOp
-
ImageDatasetExportDataOp
-
ImageDatasetImportDataOp
-
TabularDatasetCreateOp
-
TabularDatasetExportDataOp
-
TextDatasetCreateOp
-
TextDatasetExportDataOp
-
TextDatasetImportDataOp
-
TimeSeriesDatasetCreateOp
-
TimeSeriesDatasetExportDataOp
-
VideoDatasetCreateOp
-
VideoDatasetExportDataOp
-
VideoDatasetImportDataOp
API reference
For dataset component reference, see the Google Cloud Pipeline Components SDK reference for Dataset components.
For Vertex AI API reference, see the following API reference pages:
Tutorials
- Learn how to use the Google Cloud pipeline components to train an image classification model using Vertex AI AutoML.
- Learn how to use the Google Cloud pipeline components to train a classification model using tabular data and Vertex AI AutoML.
- Learn how to use the Google Cloud pipeline components to train a linear regression model using tabular data and Vertex AI AutoML.
- Learn how to use the Google Cloud pipeline components to train a text classification model using Vertex AI AutoML.
- Learn how to use the Google Cloud pipeline components to upload and deploy a model.
Version history and release notes
To learn more about the version history and changes to the Google Cloud Pipeline Components SDK, see the Google Cloud Pipeline Components SDK Release Notes.
Technical support contacts
If you have any questions, reach out to kubeflow-pipelines-components@google.com.